6 ms·

> But moving in a line, no matter how much overlap of the features you get, just doesn't work that well, and I do not understand why. How far apart were the ph

> But moving in a line, no matter how much overlap of the features you get, just doesn't work that well, and I do not understand why. How far apart were the photos taken? I think OpenDroneMap needs lots of overlap with drone photos, and even more with spherical photos to extract features well. I haven't experimented with a non-360 degree camera - the benefit of a 360 degree camera is you effectively double the photos you get (front/back). Cycling or walking also ensures huge overlap.

Enginerrrd 4y ago
I can confidently say that sufficient overlap was not the issues. I experimented a lot, but I definitely had well over 99% overlap on some runs without really any improvement. I suspect it has to do with the training data used for feature matching.
dylan604 4y ago
When you said 360 camera, I had forgotten about the el cheapo versions with only 2 lenses. I'm used to 8-16 lens setups doing live action 360 VR video. It's been years now since I was involved in that, but the 16 camera system was the one from Google, and because of the extreme overlap, every object was visible in at least 4 lenses at any time. Because of this, it was some of the most compelling 3D available at the time. Funny, with 16 cameras each with their own microSD card that had to be data managed (puke), we felt it wasn't enough as it only produced a cylindrical output and not a full sphere. So, like the glutton for punishment fools we were, we mounted an additional 6 cameras to the rig to capture the zenith/nadir and would stitch/composite into the final. All of that to say, generating 3D photogrammetry images was something we never even considered as a purpose of the footage. We were soley focused on creating VR content. Never mind that some of us involved absolutely would acquire footage for the sole purpose of creating 3D models to be used in SFX for post work. I guess sometimes, you're just too close to something to see it?!?!

Enginerrrd 4y ago

I can confidently say that sufficient overlap was not the issues. I experimented a lot, but I definitely had well over 99% overlap on some runs without really any improvement. I suspect it has to do with the training data used for feature matching.

dylan604 4y ago

When you said 360 camera, I had forgotten about the el cheapo versions with only 2 lenses. I'm used to 8-16 lens setups doing live action 360 VR video. It's been years now since I was involved in that, but the 16 camera system was the one from Google, and because of the extreme overlap, every object was visible in at least 4 lenses at any time. Because of this, it was some of the most compelling 3D available at the time. Funny, with 16 cameras each with their own microSD card that had to be data managed (puke), we felt it wasn't enough as it only produced a cylindrical output and not a full sphere. So, like the glutton for punishment fools we were, we mounted an additional 6 cameras to the rig to capture the zenith/nadir and would stitch/composite into the final. All of that to say, generating 3D photogrammetry images was something we never even considered as a purpose of the footage. We were soley focused on creating VR content. Never mind that some of us involved absolutely would acquire footage for the sole purpose of creating 3D models to be used in SFX for post work. I guess sometimes, you're just too close to something to see it?!?!